1. Field of the Invention
The present invention relates to an image collating apparatus, an image collating method, an image collating program and a computer readable recording medium recording the image collating program. More specifically, the present invention relates to an image collating apparatus, an image collating method, an image collating program and a computer readable recording medium recording the image collating program for collating two images with each other.
2. Description of the Background Art
Conventional methods of collating fingerprint images can be classified broadly into image feature matching method and image-to-image matching method. In the former, image feature matching, images are not directly compared with each other but features in the images are extracted and the extracted image features are compared with each other, as described in KOREDE WAKATTA BIOMETRICS (This Is Biometrics), edited by Japan Automatic Identification Systems Association, OHM sha, pp.42-44. When this method is applied to fingerprint image collation, minutiae (ridge characteristics of a fingerprint that occur at ridge bifurcations and ending, and few to several minutiae can be found in a fingerprint image) such as shown in FIGS. 29A and 29B serve as the image feature. According to this method, minutiae are extracted by image processing from images such as shown in FIGS. 30A to 30D; based on the positions, types and ridge information of the extracted minutiae, a similarity score is determined as the number of minutiae of which relative position and direction match among the images; the similarity score is incremented/decremented in accordance with match/mismatch in, for example, the number of ridges traversing the minutiae;. and the similarity score thus obtained is compared with a predetermined threshold for collation and identification.
In the latter method, that is, in image-to-image matching, from images “α” and “β” to be collated with each other shown in FIGS. 31A and 31B, partial images “α1” and “β1”, that may correspond to the full area or partial area, are extracted as shown in FIGS. 31C and 31D; matching score between partial images “α1” and “β1” is calculated based on total sum of difference values, correlation coefficient, phase correlation method or group delay vector method, as the similarity score between images “α” and “β”; and the calculated similarity score is compared with a predetermined threshold for collation and identification.
Inventions utilizing the image-to-image matching method have been disclosed, for example, in Japanese Patent Laying -Open No. 63-211081 and Japanese Patent Laying-Open No.63-78286. In the invention of Japanese Patent Laying-Open No. 63-211081, first, an object image is subjected to image-to-image matching, the object image is then divided into four small areas, and in each divided area, positions that attain maximum matching score in peripheral portions are found, and an average matching score is calculated therefrom, to obtain a corrected similarity score. This approach addresses distortion or deformation of fingerprint images that inherently occur at the time the fingerprints are collected. In the invention of Japanese Patent Laying-Open No. 63-78286, one fingerprint image is compared with a plurality of partial areas that include features of the one fingerprint image, while substantially maintaining positional relation among the plurality of partial areas, and total sum of matching scores of the fingerprint image with respective partial areas is calculated and provided as the similarity score.
Generally speaking, the image-to-image matching method is more robust to noise and finger condition variations (dryness, sweat, abrasion and the like), while the image feature matching method enables higher speed of processing then the image-to-image matching as the amount of data to be compared is smaller.
In an image collating process described in Japanese Patent Laying-Open No. 2003-323618, when two images are collated with each other, for each of a plurality of partial areas of one image, the whole area of the other image is searched to identify a position of a partial image that has the maximum matching score. Therefore, there has been a significant burden on computing the position having the maximum matching score. This makes it difficult to realize high speed collation.
At present, biometrics-based technique of personal authentication as represented by fingerprint authentication is just beginning to be applied to consumer products. In this early stage of diffusion, it is desired to make as short as possible the time for personal authentication. Further, for expected application of such authentication function to a personal portable telephone or to a PDA (Personal Digital Assistants), shorter time and smaller power consumption required for authentication are desired, as the battery capacity is limited.